MIT's new fine-tuning method lets LLMs learn new skills without losing old ones

MIT researchers developed a technique called SDFT, enabling large language models to learn new skills without forgetting old ones. SDFT allows models to accumulate multiple skills over time, addressing the challenge of continual learning. This method offers a pathway for building adaptive AI agents.